CN101861126B - Visualization of vascularization - Google Patents
Visualization of vascularization Download PDFInfo
- Publication number
- CN101861126B CN101861126B CN2008801166172A CN200880116617A CN101861126B CN 101861126 B CN101861126 B CN 101861126B CN 2008801166172 A CN2008801166172 A CN 2008801166172A CN 200880116617 A CN200880116617 A CN 200880116617A CN 101861126 B CN101861126 B CN 101861126B
- Authority
- CN
- China
- Prior art keywords
- image space
- data
- space data
- pathological changes
- image
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012800 visualization Methods 0.000 title description 2
- 230000002792 vascular Effects 0.000 claims abstract description 49
- 231100000915 pathological change Toxicity 0.000 claims description 53
- 230000036285 pathological change Effects 0.000 claims description 53
- 238000000034 method Methods 0.000 claims description 27
- 238000005516 engineering process Methods 0.000 claims description 13
- 238000005520 cutting process Methods 0.000 claims description 7
- 230000002093 peripheral effect Effects 0.000 claims description 5
- 230000003902 lesion Effects 0.000 abstract description 6
- 210000004204 blood vessel Anatomy 0.000 description 22
- 238000002591 computed tomography Methods 0.000 description 12
- 206010028980 Neoplasm Diseases 0.000 description 11
- 230000000007 visual effect Effects 0.000 description 8
- 230000008859 change Effects 0.000 description 6
- 238000007689 inspection Methods 0.000 description 6
- 230000002685 pulmonary effect Effects 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 4
- 238000002600 positron emission tomography Methods 0.000 description 4
- 210000001519 tissue Anatomy 0.000 description 4
- 230000036770 blood supply Effects 0.000 description 3
- 230000000873 masking effect Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000009877 rendering Methods 0.000 description 3
- 201000011510 cancer Diseases 0.000 description 2
- 238000013170 computed tomography imaging Methods 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000002603 single-photon emission computed tomography Methods 0.000 description 2
- 238000000638 solvent extraction Methods 0.000 description 2
- BSYNRYMUTXBXSQ-UHFFFAOYSA-N Aspirin Chemical compound CC(=O)OC1=CC=CC=C1C(O)=O BSYNRYMUTXBXSQ-UHFFFAOYSA-N 0.000 description 1
- 210000003484 anatomy Anatomy 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 210000000988 bone and bone Anatomy 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 239000002872 contrast media Substances 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 230000003387 muscular Effects 0.000 description 1
- 230000000505 pernicious effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 230000035807 sensation Effects 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
- 238000007794 visualization technique Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/08—Volume rendering
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
- A61B6/03—Computed tomography [CT]
- A61B6/032—Transmission computed tomography [CT]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/12—Arrangements for detecting or locating foreign bodies
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/50—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications
- A61B6/504—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications for diagnosis of blood vessels, e.g. by angiography
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T19/00—Manipulating 3D models or images for computer graphics
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4887—Locating particular structures in or on the body
- A61B5/489—Blood vessels
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10081—Computed x-ray tomography [CT]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2210/00—Indexing scheme for image generation or computer graphics
- G06T2210/41—Medical
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- Medical Informatics (AREA)
- Theoretical Computer Science (AREA)
- Heart & Thoracic Surgery (AREA)
- Public Health (AREA)
- Biophysics (AREA)
- High Energy & Nuclear Physics (AREA)
- General Physics & Mathematics (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Optics & Photonics (AREA)
- Pathology (AREA)
- Radiology & Medical Imaging (AREA)
- Biomedical Technology (AREA)
- Veterinary Medicine (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Computer Graphics (AREA)
- Software Systems (AREA)
- Geometry (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Computer Hardware Design (AREA)
- General Engineering & Computer Science (AREA)
- Pulmonology (AREA)
- Vascular Medicine (AREA)
- Dentistry (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Apparatus For Radiation Diagnosis (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
- Image Processing (AREA)
- Magnetic Resonance Imaging Apparatus (AREA)
Abstract
An apparatus produces image space data (35) indicative of the spatially varying strength of the vascular connections between locations in the image space and a lesion or other feature of interest. The data may be presented by way of a maximum intensity projection (MIP) display in which the brightness of the image represents the strength of the vascular connection.
Description
The application relates to visual that vascular forms.It especially be applied in computed tomography (CT) view data to tumor vessels form carry out visual.The present invention also more generally relates to and carries out visual to the connectedness of other pathological changes or feature of interest in the image space data of using other imaging form to generate.
In such as the medical diagnosis on disease of cancer and treatment, played the part of the key player such as the imaging of medical form of CT, magnetic resonance (MR), ultrasonic (US), single photon emission computed tomography (SPECT), PET (positron emission tomography) (PET) and x ray.Can be that its vascular forms for assessment of a factor of tumor or other suspicious lesions.Therefore, the pathological changes degree that is connected to peripheral vascular system and mode can for the clinician provide such as with about determining that this tumor is optimum or pernicious, the relevant useful information such as it may be grown.
Unfortunately, many factors make that vascular (vascular) is visual may be very complicated.For example, although many blood vessels may be positioned near the tumor, be not that in them all can help the pathological changes blood supply.In addition, various blood vessel brightness may be different with size.Even less blood vessel has vascular to contact with this tumor, also often may relatively be difficult for observing and having lower contrast.Although larger blood vessel may be fine visual, may have with this tumor have seldom or do not have vascular to be connected.
Used and cut apart with relevant surfaces rendering technique identification and be those voxels of representing blood vessel.Yet unfortunately, the result of cutting operation is generally responsive to partitioning algorithm and selected partitioning parameters.For example, luminance threshold, noise suppressed and minimum thickness standard all may affect whether particular configuration is identified as blood vessel.
Many aspects of the present invention have solved these and other problem.
According to first aspect, a kind of method is provided, the method comprises to be assessed the first image space data that comprise pathological changes and vascular system, thus the spatial variations intensity that vascular connects between each position in definite this first image space and this pathological changes.The method also comprises the second image space data that generate the determined spatial variations intensity of indication.
According to another aspect, a kind of equipment is provided, comprise for the first image space data that comprise pathological changes are assessed, to determine the device of the spatial variations intensity of vascular connectedness between this each position of the first image space and the pathological changes.This equipment also comprises the device for the second space modified-image spatial data that generates the determined intensity of indication.
According to another aspect, computer-readable recording medium comprises a plurality of instructions, makes this processor carry out such method when carrying out these instructions by processor.The method comprises to be assessed the first image space data that comprise feature of interest, with the spatial variations intensity that vascular connects between each position and this feature in definite this first image space, and generate the second image space data of indicating determined spatial variations intensity.
According to another aspect, a kind of equipment is provided, it comprises for the device of identifying the mulitpath of the vascular connection that may represent this object pathological changes in the image space data of denoted object.This equipment also comprises the device that changes the vascular connection data for the span, and this spatial variations vascular connection data representative is connected to the probability of this pathological changes via this path vascular along each position in this path.
After reading and having understood drawing and description, those skilled in the art will recognize other each side of the present invention.
Description of drawings
Be to be limited to accompanying drawing to describe the present invention by way of example and not, wherein, similar label is indicated similar part, and wherein:
Fig. 1 has described a kind of CT scanner;
Fig. 2 has described a kind of method;
Fig. 3 A-Fig. 3 E has described image space data and associated picture;
Fig. 4 has described a kind of method.
With reference to figure 1, CT scanner 10 comprises the rotary frame 18 of 14 rotations around the inspection area.The x radiographic source 12 that this rotary frame 18 is supported such as the x ray tube.This frame 18 is also supported x ray sensitive detectors 20, and its circular arc is facing to inspection area 14.The x ray that is generated by x radiographic source 12 passes inspection area 14 and is detected by detector 20.According to the configuration of scanner 10 and detector 20, it is fan-shaped, wedge or conical radiation beam substantially that x radiographic source 12 generates, its coverage extension same space general and detector 20.Therefore, scanner 10 generates data for projection, and its indication is along many projections by being placed on object in the inspection area 14 or the attenuation of ray.Such as the supporter 16 of sick bed in the inspection area 14 inner support patients or other objects.
Be positioned on the rotary frame 18 or the data measurin system 23 of contiguous rotary frame 18 receives signals from detector 20, and necessary analog to digital conversion, multiplexing, interface, data communication and similar functions are provided.
The data for projection that reconstructor 22 data reconstruction measuring systems 23 gather is to generate the image space data 24 of indication patient internal anatomy.Also will understand, also can fulfil filtering, enhancing and/or other image processing operations to the image space data.
Noticing aforementioned is the example of a suitable CT scanner configuration, and can expect other configuration.For example, in the configuration of the 4th generation, detector 20 general maintenances are fixing, and rotary frame part 18 is around the inspection area rotation.The x radiographic source can be configured to other form except traditional x ray tube, use the electronics wave beam scanner of electronics wave beam also to expect.In addition, the spectral CT system can provide the information about the subject material composition.The common staff of those of this area will understand it also can have other variation.
Usually image space data 24 are arranged as three-dimensional (3D) voxel array 21.Each voxel has the value that changes according to measured variable.In the situation that the CT view data, measured variable is the x ray attenuation normally, and its value conventionally represents with Hounsfield unit (HU).Like this, voxel value is usually with the attenuation that changes on the representative object space.
Continuation is with reference to Fig. 1, and volume of interest (VOI) extractor 26 extracts or otherwise volume of interest or other area-of-interest 24 of selection image space data.For the purpose of this discussion, suppose the VOI and at least a portion peripheral vascular system that use VOI selector 26 to select to comprise tumor, tuberosity or other pathological changes interested.VOI extractor 26 can be based on extracting VOI from user's manual input, suitable automated characterization detection technique, semi-automatic or another kind of suitable form.
Can use masking structure remover 28 from the image space data, to remove such as the covering or interference structure of bone, adjacent tissue etc., to generate VOI data 29.Equally, can manually, automatically use suitable cut apart and/or structure removes technology, semi-automatic or fulfil masking structure with the suitable form of another kind and remove by the user.
30 pairs of image space data of pathological changes evaluator are processed, thereby identification VOI data 29 are corresponding to those parts of pathological changes 31 interested.In one implementation, pathological changes evaluator 30 comprises the dispenser that adopts known cutting techniques that pathological changes interested is cut apart.Equally, can be automatically, manual, semi-automatic or fulfil pathological changes identification with the suitable form of another kind by the user.
32 pairs of VOI data 29 of vascular Path Recognition device are processed, and pass through path image space, that represent the possible vascular connection of pathological changes with identification.In one implementation, and following further discussion, this Path Recognition device 32 utilize region growing (prioritized regiongrowing) technology priority of distinguishing orders of priority identify those by image space, most probable represents the path that the strong vascular of pathological changes connects.
34 pairs of paths of identifying of vascular path analysis device are analyzed, with identification along identify path, representative arrives the relatively position of weak pulse pipe connection of pathological changes.More particularly, in one embodiment, for each position in the image space, this path analysis device 34 determine along definite path in pathological changes and represent position between the weak pulse pipe link position.
Vascular connectivity data generator 36 generates in the representative image spaces vascular connectivity data 35 of vascular contiguity between each position and pathological changes or intensity.More specifically, the connectivity data 35 that these number generator 36 spans change, wherein, the value that conforms to position in this connectivity data 35 depends on the value in path analysis device 34 determined position VOI data 29.
Maximum intensity projection (MIP) 38 pairs of VOI data 29 of generator operate, thereby generate the VOI MIP data 39 of passing through these VOI data 29 for one or more angles or projection
1-NMIP generator 38 also operates vascular connectivity data 36, thereby generates connective MIP data 40 for the homolographic projection by this vascular connectivity data 35
1-NFor the situation of VOI MIP data 39, the value that the brightness of each position representative runs in VOI data 39 in the image projection.For connective MIP data 40
1-NSituation, these value representatives are to intensity or the degree of pathological changes connectedness interested.For demonstration and/or the comparison that helps two data sets, can be with same units (for example, CT number or the HU under the CT data cases) expression voxel value.
42 pairs of MIP data 39 of image processor
1-N, connective MIP data 40
1-N, and the pathological changes data 31 of cutting apart process, in order to present via display, monitor or other suitable man machine interface 91.Simultaneously in order to help comparison, for example, can on interface 91, show simultaneously VOI MIP data 39 and connective MIP data 40 based on mode side by side.For example, by the shown MIP image of rotation in about the coordinate of suitable rotating shaft, MIP data 39,40 can also be rendered as motion MIP and show.In one example, rotate back and forth image by approximately positive and negative ten (10) angles of spending and give three-dimensional sensation.In another example, rotate periodically MIP by 360 degree.Replacedly, for example, can also offer an opportunity with spin data as desired to the user, for example through window and level, rotation or the control of other user-operable.
In connection with Fig. 2 operation is described now.
At 202 places, the patient is scanned to generate data for projection.For the purpose of this discussion, with supposition recording projection data on the part in the zone that comprises at least patient pulmonary.Notice, depend on such as the factor of pathological changes type, peripheral vascular system and scanning form, scanning can be combined with the introducing of contrast agent, thereby obtain the data for projection that contrast strengthens.As when pathological changes and/or vascular system is positioned at or may occur during near heart or muscular tissue, in the situation that be difficult to distinguish part or all pathological changes or vascular system from surrounding tissue, this implementation is particularly useful.
At 204 places, rebuild this data for projection with synthetic image spatial data 24.Notice simultaneously, can fulfil reconstruction 204 and operation subsequently away from the when and where place of scan operation.
At 206 places, from image space extracting data VOI.For the purpose of this example, will suppose that VOI comprises pulmonary lesion, this pulmonary lesion is under a cloud to be that cancer and expectation are assessed the blood supply of this pathological changes.Like this, for the purpose of this example, VOI will comprise this pathological changes and the part of peripheral vascular system at least.
In Fig. 3 A, schematically show the example 29 of the VOI that has extracted.Although for convenience of explanation, the VOI 29 that has extracted is illustrated as two dimension (2D) projection, will understands, this VOI will comprise the 3D volume usually, and it comprises pathological changes 304 and vascular system 306.
Relatively large blood vessel is usually easier to be visible and seem relatively brighter in image, and the blood vessel of less may darker or more difficult distinguishing.Yet, also will recognize, the visibility of blood vessel 306 or the brightness not necessarily intensity with this vascular that is connected to pathological changes 304 are relevant.For example, the blood vessel of high-visibility may weak (if there is) be connected to pathological changes 304, thereby these pathological changes 304 blood supplies are played seldom effect or inoperative.On the other hand, the blood vessel of low visibility may be connected to by force pathological changes 304.For the purpose of this example, will suppose blood vessel 306
CBe connected to relatively by force pathological changes 304, and blood vessel 306
DThe weak connection.
If occur masking structure in the view data, can it be removed from view data at step 208 place.
At 210 places, for example, use suitable cutting techniques identification pathological changes.Generally by the pathological changes 31 of the diagram of the shade among Fig. 3 B through cutting apart.
Generate the vascular connectivity data at step 212 place, schematically illustrate the example of voxel connectivity data 35 at Fig. 3 C place.More specifically, each position in the connectivity data 35 or voxel receive such value, and this value represents it to pathological changes 304 vascular bonding strengths; Each voxel in this connectivity data 35 receives such data value, and this data value equals the minimum voxel value that most probable vascular path runs between this pathological changes 304 and this voxel.Therefore, in this example, blood vessel 306
CRelatively " brighter ", and blood vessel 306
DThen be not.In other words, suppress the blood vessel 306 that those are not connected to by force pathological changes relatively
D
Generate respectively MIP data 39,40 by connectivity data 35 and VOI data 29 at step 214 place for one or more projections.Schematically illustrate the MIP data 39,40 for the example projection at Fig. 3 D place.
At 216 places, on the MIP data 39,40 that the pathological changes 31 through cutting apart can be added to.
At step 218 place MIP data 39,40 are presented to the user.In the implementation that in Fig. 3 E, schematically illustrates, present side by side MIP data 39,40 for the homolographic projection by image space through man machine interface 91.As mentioned above, the projection that 310 rotations present about suitable rotating shaft can generate motion MIP and show.
Referring now to Fig. 4 the generation of vascular connectivity data 35 is described further, it has illustrated the region growing technology of the differentiation order of priority of example, wherein, the minimum brightness of the brightness of voxel representative voxel in the strongest vascular path, edge between pathological changes and this voxel in the connectivity data 35.
At 402 places, to identifying at borderline those voxels of pathological changes (that is, its first order is contiguous) and it being considered as candidate's voxel.
At 404 places, the probability that represents blood vessel according to candidate's voxel sorts to them.
Notice and to use various probability standards.According to a kind of technology, according to the relative data value of candidate's voxel they are sorted, for example at first consider relatively high value.This technology is particularly useful under the situation such as pulmonary lesion CT imaging, and wherein, the voxel that represents blood vessel in pulmonary lesion CT imaging is compared relative contrasty with surrounding tissue strong.In a kind of variant, can only consider those voxels in certain scope, according to the position of those voxels in this scope they are sorted.Additionally or alternatively, can use morphology or out of Memory.Those skilled in the art will recognize, above-mentionedly only be examples and can adopt other suitable variant.In addition, can adopt path generation technique except region growing.
At 406 places, the access most probable represents candidate's voxel of blood vessel.
At 408 places, add accessed voxel to path.Notice, represent the probability of blood vessel and the position of accessed voxel according to accessed voxel, can add accessed voxel to existed path, with its beginning that is considered as the branch in existing path or consists of new path.
At 410 places, if accessed voxel is least may represent the voxel that pathological changes connects along current path, be set to so the value of accessed pixel for the probability value in the path of current path.In the situation of the CT data that represent VOI data 29 with HU, can represent path probability value with HU equally.
At 412 places, its position is set to current path probability value corresponding to the voxel of accessed voxel location in the connectivity data 35.
At 414 places, the first order vicinity of accessed voxel is identified.
At 416 places, for example, as desired, repeat this process until accessed all voxels of the first image space 29.
An advantage of above-mentioned technology is to represent with the relative brightness of blood vessel connective degree.In addition, visualization process does not rely on the intrinsic binary decision that whether is connected to tumor about particular blood vessel.With respect to surface rendering, the MIP projection does not generally need luminance threshold yet, relatively still less tend to dim structure (fainter structure) and suppress, and trend towards about picture noise more sane.
Also will understand, the order of each step can change.For example, do not need to generate with the path and carry out simultaneously the analysis that is connected along the most impossible vascular of given path, and it can be fulfiled in independent step.Can adopt breadth-first, depth-first and other ordering techniques.Can also use the technology except region growing that the path is identified.
It is also contemplated that other variation.For example, above-mentioned technology is not limited to the CT data, and can include but not limited to that the view data that other form of MR, US, SPECT, PET and x ray generates is combined with above-mentioned technology with use.Can also be combined with them with the pathological changes except tumor and tuberosity, and can carry out visual to the connectedness to structure except pathological changes.Can also adopt them to carry out visual to the connectedness except the vascular connectedness.
Also can expect and use various demonstrations and visualization technique.As an example, can use the volume rendering technology to present connectivity data 35.As another example, can represent by the mode of color change or shade connective brightness value.
Should be appreciated that, can realize above-mentioned various technology through the multiple combination of hardware and/or computer software or firmware.In the situation that software, firmware etc. can be stored in computer-readable instruction on the computer-readable recording medium.When being carried out by computer processor, these instructions make processor realize described technology.For example, by download these instructions through the Internet, instruction can also be positioned at long-range and as required access.
Invention has been described with reference to preferred embodiment.After reading and having understood above stated specification, can make amendment and change it.The present invention is intended to be interpreted as comprising all such modifications and change, as long as these modifications and change are in claims or its equivalent scope.
Claims (15)
1. the method for a synthetic image spatial data comprises:
The the first image space data (24,29) that comprise pathological changes (304) and vascular system (306) are assessed the spatial variations intensity that connects with vascular between the tissue of determining the position in the first image space and the described pathological changes; And
Generate the second image space data (35) of the determined spatial variations intensity of indication.
2. the method for claim 1 also comprises presenting the image of indicating described the second image space data, and wherein, the image that presents comprises the spatial variations characteristic of indicating determined spatial variations intensity.
3. method as claimed in claim 2, wherein, described characteristic comprises brightness.
4. the method for claim 1, wherein described method also comprises:
In described the first image space data (29), the identification representative is to the first path of the possible vascular connection of described pathological changes (304), and wherein, described path comprises primary importance;
Represent the second position that relative weak pulse pipe connects between described primary importance and the described pathological changes along described Path Recognition.
5. method as claimed in claim 4, wherein, described the first image space data denoted object, and described method comprises also in described the second image space data that the value corresponding to the position of described primary importance is set to indicate the value of stating the measured characteristic of object in described second position place.
6. method as claimed in claim 5, wherein, described characteristic comprises the x ray attenuation.
7. method as claimed in claim 4, wherein, the strongest vascular that described the first path represents between described primary importance and the described pathological changes connects, and the representative of the described second position connects along the weak pulse pipe in described the first path.
8. the method for claim 1 also comprises the MIP data (40) that generate described the second image space data of indication.
9. method as claimed in claim 8 also comprises:
Generate the MIP data (39) of described the first image space data of indication; And
Simultaneously present the described MIP data of indicating described the first image space data and the described MIP data of indicating the second image space data with the appreciable form of the mankind.
10. the method for claim 1 comprises:
From described the first image space data of the 3rd image space extracting data of denoted object, wherein, described the 3rd image space data comprise at least a portion of the peripheral vascular system of described pathological changes and described pathological changes;
Cut apart described pathological changes; And
Present the pathological changes of indication through cutting apart and the image of described the second image space data.
11. the device of a synthetic image spatial data comprises:
Be used for the first image space data (24,29) that comprise feature of interest (304) are assessed the module of the spatial variations intensity that connects with vascular between the tissue of determining described the first image space position and the described feature; And
Be used for generating the module of the second image space data (35) of indicating determined spatial variations intensity.
12. device as claimed in claim 11, wherein, described device also comprises:
Be used for presenting the module of the image of indicating described the second image space data, wherein, described image comprises the spatial variations brightness that represents described spatial variations intensity.
13. device as claimed in claim 11, wherein, described device also comprises the module for the MIP data that generate described the second image space data of indication.
14. device as claimed in claim 11, wherein, described device also comprises:
Be used for identification by the module in the possible vascular path of described the first image space;
Be used for identification represents the position of relative weak pulse pipe connection along described path module; And
The the first image space data that are used for use institute recognizing site place produce the module of described the second image space data.
15. device as claimed in claim 11, wherein, described the first image space data denoted object, and described device also comprises:
Be used for using region growing technology to identify the module in the vascular path between described feature and the primary importance;
Be used for identification represents between described feature and the described primary importance second position of weak pulse pipe position along described path module; And
The position that is used for described the second image space data is set to represent the module of stating the value of the measured characteristic of object in described second position place.
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US98913407P | 2007-11-20 | 2007-11-20 | |
| US60/989,134 | 2007-11-20 | ||
| PCT/IB2008/054592 WO2009066195A1 (en) | 2007-11-20 | 2008-11-04 | Visualization of vascularization |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN101861126A CN101861126A (en) | 2010-10-13 |
| CN101861126B true CN101861126B (en) | 2013-02-13 |
Family
ID=40385506
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2008801166172A Active CN101861126B (en) | 2007-11-20 | 2008-11-04 | Visualization of vascularization |
Country Status (6)
| Country | Link |
|---|---|
| US (1) | US8588492B2 (en) |
| EP (1) | EP2211717B1 (en) |
| JP (1) | JP5616229B2 (en) |
| CN (1) | CN101861126B (en) |
| RU (1) | RU2488351C2 (en) |
| WO (1) | WO2009066195A1 (en) |
Families Citing this family (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB0910138D0 (en) * | 2009-06-12 | 2009-07-29 | Siemens Medical Solutions | Combination of MIP and anatomical information |
| FR2963976B1 (en) * | 2010-08-23 | 2013-05-10 | Gen Electric | IMAGE PROCESSING METHOD FOR DETERMINING SUSPECTED ZONES IN A TISSUE MATRIX, AND ITS USE FOR 3D NAVIGATION THROUGH THE TISSUE MATRIX |
| WO2012176100A1 (en) * | 2011-06-22 | 2012-12-27 | Koninklijke Philips Electronics N.V. | System and method for processing a medical image |
| WO2013038452A1 (en) * | 2011-09-15 | 2013-03-21 | 株式会社島津製作所 | Medical data processing device and radiation tomography device provided therewith |
| WO2015042519A2 (en) * | 2013-09-20 | 2015-03-26 | Mayo Foundation For Medical Education And Research | Systems and methods for producing imaging biomarkers indicative of a neurological disease state using gray matter suppression via double inversion-recovery magnetic resonance imaging |
| US10074207B2 (en) * | 2014-05-19 | 2018-09-11 | Koninklijke Philips N.V. | Visualization of tissue of interest in contrast-enhanced image data |
| TWI573561B (en) * | 2014-11-25 | 2017-03-11 | 正崴精密工業股份有限公司 | Vital sign measurement system and method, and earphone thereof |
| CN109475338B (en) * | 2016-07-15 | 2023-01-17 | 皇家飞利浦有限公司 | Identifying types of adipose tissue |
| JP2020508713A (en) * | 2017-02-27 | 2020-03-26 | コーニンクレッカ フィリップス エヌ ヴェＫｏｎｉｎｋｌｉｊｋｅ Ｐｈｉｌｉｐｓ Ｎ．Ｖ． | Vein puncture and arterial line guide by signal fluctuation amplification |
| CN107038747B (en) * | 2017-03-31 | 2021-08-06 | 北京全域医疗技术集团有限公司 | Medical image file multi-plane processing method and device |
| CN110123453B (en) * | 2019-05-31 | 2021-07-23 | 东北大学 | Operation navigation system based on unmarked augmented reality |
| CN114340497A (en) * | 2019-10-30 | 2022-04-12 | 未艾医疗技术(深圳)有限公司 | Intestinal tumor and blood vessel analysis method based on VRDS AI medical image and related device |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101028198A (en) * | 2006-01-17 | 2007-09-05 | 西门子公司 | Method for examining vascular of patient based on image data in inspection region |
Family Cites Families (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH07262352A (en) * | 1994-03-25 | 1995-10-13 | Ge Yokogawa Medical Syst Ltd | Continuous object discriminating method and three-dimensional image display device |
| US5752522A (en) * | 1995-05-04 | 1998-05-19 | Cardiovascular Concepts, Inc. | Lesion diameter measurement catheter and method |
| US6058218A (en) * | 1997-11-10 | 2000-05-02 | General Electric Company | Enhanced visualization of weak image sources in the vicinity of dominant sources |
| US6549798B2 (en) | 2001-02-07 | 2003-04-15 | Epix Medical, Inc. | Magnetic resonance angiography data |
| JP4083115B2 (en) * | 2001-06-15 | 2008-04-30 | ザ トラスティーズ オヴ ザ ユニヴァーシティー オヴ ペンシルバニア | Functional brain imaging to discover and evaluate lies and hidden perceptions, and cognitive / emotional responses to information |
| ES2185493B1 (en) | 2001-07-03 | 2004-06-16 | Madrid Genetics, S.L. | METHOD FOR EVALUATING IN VITRO IN RELEVANT PHYSIOLOGICAL OR PATHOLOGICAL CONDITIONS THE BIOLOGICAL ACTIVITY OF LARGE-SCALE COMPOUNDS. |
| US6609021B1 (en) | 2002-05-20 | 2003-08-19 | Siemens Corporate Research, Inc. | Pulmonary nodule detection using cartwheel projection analysis |
| JP2004008304A (en) * | 2002-06-04 | 2004-01-15 | Hitachi Ltd | Method for generating and displaying three-dimensional shape using multidirectional projection image |
| DE102004028123B4 (en) * | 2004-06-09 | 2008-06-26 | Siemens Ag | Computer tomograph with a Messanordung and an image calculator for generating a three-dimensional image data set of a body part of a patient |
| EP1815435A4 (en) * | 2004-10-01 | 2011-05-11 | Cedara Software Corp | Blood vessel structures segmentation system and method |
| US7532748B2 (en) | 2004-11-24 | 2009-05-12 | General Electric Company | Methods and apparatus for selecting and/or labeling vessel branches |
| EP1877980A2 (en) * | 2004-12-22 | 2008-01-16 | Bio-Tree Systems, Inc. | Medical imaging methods and apparatus for diagnosis and monitoring of diseases and uses therefor |
| CN101120381B (en) * | 2005-02-14 | 2012-09-26 | 皇家飞利浦电子股份有限公司 | Apparatus and method for determining an injection point for targeted drug delivery |
| EP1894164A2 (en) * | 2005-06-24 | 2008-03-05 | Edda Technology, Inc. | Methods for interactive liver disease diagnosis |
| US7747051B2 (en) * | 2005-10-07 | 2010-06-29 | Siemens Medical Solutions Usa, Inc. | Distance transform based vessel detection for nodule segmentation and analysis |
| JP4916386B2 (en) * | 2007-06-13 | 2012-04-11 | 株式会社日立メディコ | X-ray CT system |
-
2008
- 2008-11-04 US US12/742,157 patent/US8588492B2/en active Active
- 2008-11-04 EP EP08851497.1A patent/EP2211717B1/en active Active
- 2008-11-04 CN CN2008801166172A patent/CN101861126B/en active Active
- 2008-11-04 JP JP2010533684A patent/JP5616229B2/en active Active
- 2008-11-04 WO PCT/IB2008/054592 patent/WO2009066195A1/en active Application Filing
- 2008-11-04 RU RU2010125247/14A patent/RU2488351C2/en not_active IP Right Cessation
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101028198A (en) * | 2006-01-17 | 2007-09-05 | 西门子公司 | Method for examining vascular of patient based on image data in inspection region |
Also Published As
| Publication number | Publication date |
|---|---|
| RU2488351C2 (en) | 2013-07-27 |
| CN101861126A (en) | 2010-10-13 |
| RU2010125247A (en) | 2011-12-27 |
| EP2211717B1 (en) | 2014-01-08 |
| US20100278408A1 (en) | 2010-11-04 |
| JP5616229B2 (en) | 2014-10-29 |
| JP2011502680A (en) | 2011-01-27 |
| WO2009066195A1 (en) | 2009-05-28 |
| EP2211717A1 (en) | 2010-08-04 |
| US8588492B2 (en) | 2013-11-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101861126B (en) | Visualization of vascularization | |
| JP5039294B2 (en) | Apparatus and method for analyzing tissue type along a cylindrical structure | |
| EP1526808B1 (en) | Systems for detecting components of plaque | |
| US6922462B2 (en) | Method, system and computer product for plaque characterization | |
| JP4412982B2 (en) | Method and apparatus for quantifying tissue fat content | |
| US7796795B2 (en) | System and method for computer aided detection and diagnosis from multiple energy images | |
| US7177453B2 (en) | Method and apparatus for partitioning a volume | |
| US7072435B2 (en) | Methods and apparatus for anomaly detection | |
| CN105934199B (en) | For handling the device and method of the medical image of body cavity | |
| EP2880594B1 (en) | Systems and methods for performing segmentation and visualization of multivariate medical images | |
| JPWO2006057304A1 (en) | X-ray CT apparatus and image processing apparatus | |
| JP7216722B2 (en) | Image feature annotation in diagnostic imaging | |
| JP6486953B2 (en) | Method for segmenting motion structure in image data, target motion structure segmenter, and storage medium | |
| JP6609091B2 (en) | CT apparatus and image processing method used by the CT apparatus | |
| JP7258744B2 (en) | spectral computed tomography fingerprinting | |
| EP4241244A1 (en) | Image rendering method for tomographic image data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |